A recent study has shown that 61% of B2B marketers are sending all of their leads to sales, and that on average only 27% of those leads have actually been qualified by marketing beforehand. As the marketing or sales leader of your organization, it is your duty not just to monitor and ensure a smooth lead qualification process and buyer journey, but to continuously analyze and enable your team to enhance the lead acquisition process, qualification process, and overall buyer experience. The issue that most leaders face during these periods of digital transformation is finding a way to enable their marketing and sales teams without the need for additional budget. Enter the augmented workforce.
Lead Scoring & The Manual Qualification Process
Most organizations adopt a lead scoring model to allow their teams to focus their time and energy on leads that show buyer intent. This buyer intent is based on a number of characteristics including the lead’s interactions with specific content, characteristics such as the lead’s demographics, firmographics, as well as the use of historical data collected from a variety of different sources. All of this information is then collected, consolidated and analyzed in an effort to concoct a hypothesis for future behavior, which in turn, allows marketing and sales to guide them along their buyer journey.
As practical as this model may be for those 27% of leads that have been qualified as an MQL, there is still the overwhelming 73% of leads that have shown interest that have now been added to your database, are in some phase of their buying journey, and are now left to navigate the buying journey alone, all due to the organization’s inability to effectively qualify and engage with each and every lead.
Another common “quick fix” is to utilize SDR’s to comb through the database to find missed opportunities, as well as to act as a manual qualifying mechanism, to engage with leads through individual, personalized conversations. However this system is not only costly, but incredibly time and energy dependent. Not to mention it can be a real morale killer for sales teams.
With many organizations facing a similar scenario, digital transformation projects are based on technology that offers the ability to scale the lead qualification processes, optimize internal productivity, and provide personalized 1-to-1 human-like engagement with leads.
An Augmented Workforce: Using AI and Automation To Fill The Void
The concept of utilizing artificial intelligence to fill in the gaps where human error or inefficiency within an organization is pronounced,is nothing new. However in this age of digital transformation, automation and artificial intelligence have come together to bring forth the emergence of the Automated AI Assistant.
An Automated AI Assistant offers the best of both automation and artificial intelligence, providing human-like, real-time, two-way conversations, 24/7, 365 days a year.
Companies like Exceed.ai have blazed the path for Marketing and Sales teams to qualify more opportunities and find new customers by ensuring every lead is followed up, nurtured, qualified, and handed over to sales by booking a meeting in the live reps calendar.
The Automated AI Assistant works alongside humans as a virtual SDR, utilizing sales automation capabilities to follow up, re-engage, and nurture the 73% of leads who may not be sales-ready, but are interested in being led along the buyer journey. This process allows live sales reps to save valuable time and focus only on the qualified pipeline.
It is through the growing adoption of these tools, that companies like Comeet have been able to double their revenue year over year, a drastic, increase in overall internal productivity, and the qualification of new pipeline from their database of pre-existing leads, all without the need for additional headcount.